Pear VC
At Atrix, our journey began with a simple belief:
Breakthrough medicines and technologies change lives, and the people making them deserve better tools.
We often celebrate the final moment: a patient receiving a life-saving therapy or a groundbreaking treatment becoming standard of care. But behind that moment is a complex, coordinated effort that begins years earlier.
Pharmaceutical and med device companies shoulder this responsibility every day:
Advancing science from lab to clinic Navigating regulatory and access barriers Ensuring safe, evidence-based adoption in the real world They're not just bringing products to market; they're shaping the future of care.
Yet these organizations are often held back by outdated workflows and siloed data, unable to fully harness the knowledge that already exists across their teams.
Atrix was built to change that.
We exist to support the mission of those who dedicate their lives to creating and delivering innovations that impact global health.
The Role Description
You'll be a
core builder of Atrix's backend infrastructure , powering AI-native workflows that ingest unstructured data, structure it with AI, and deliver insights that matter-instantly and reliably.
You'll work on
scalable data pipelines, robust APIs, and real-time inference systems , supporting everything from complex agent workflows to customer-facing dashboards. Whether it's building retrieval pipelines, optimizing async background workers, or designing clean, secure APIs, your work will be foundational to how our platform works and scales.
We're building a
modular, agentic platform
that connects to customer-approved data sources, transforms unstructured data using LLM-based agents, and delivers decision-ready intelligence to regulated teams.
You'll tackle rich backend engineering challenges like:
System Design & Reliability
- Scale to handle massive amounts of records with fast response times LLM Ops
- Make AI outputs explainable, auditable, and efficient Multi-Tenant Infra
- Isolate customer data across parallelized pipelines AI Performance Tuning
- Optimize inference cost, caching, and latency RAG Pipelines & Contextual Workflows
- Connect structured + unstructured data for real-world usage You'll work closely with the
Engineering Lead and CEO , and collaborate across product, AI, and GTM. As one of our
earliest backend engineers , you'll influence everything from our architecture to hiring bar.
This is an
in-person role based in NYC , with flexibility for remote work on some days as needed.
Responsibilities
This role is perfect for someone who thrives on solving deep technical problems, loves optimizing systems for speed and scale, and gets energized by seeing their work used in real-world, high-stakes environments. If you're excited about powering AI workflows behind the scenes-and building infrastructure that's as elegant as it is reliable-we'd love to talk.
In this role, you will:
Design and own major modules of our backend architecture (APIs, workers, orchestration) Optimize performance and reliability of data processing and AI inference systems Build and maintain LLM-powered backend features and multi-step workflows Collaborate with product and AI teams to launch performant, production-grade AI features Improve observability, traceability, and modularity of backend systems Lead customer-focused feature delivery with high attention to security and compliance Must haves
5+ years backend engineering experience in fast-paced product teams 2+ years of Python experience, including async programming Expertise with one or more frameworks: FastAPI, Flask, Django Strong experience with SQL (PostgreSQL) and ORMs (SQLAlchemy or equivalent) Experience building APIs, background workers, and distributed systems Understanding of how LLMs, embeddings, or RAG workflows function Startup experience or demonstrated ownership in complex backend projects Nice to haves
Familiarity with Celery, LangChain, LlamaIndex, or other LLM orchestration tools Exposure to RAG or context injection workflows Experience with AWS, Terraform, Kafka, or PyTorch Background in healthcare, data security, or regulated environments Why Join Atrix as a Backend Engineer?
Mission-Driven Impact Your code will help life sciences teams deliver better treatments-faster. Every system you build supports real-world clinical outcomes.
Real AI, Real Stakes This isn't research tooling. You'll make AI work for real customers-ensuring reliability, explainability, and speed in high-stakes environments.
Deep Backend Ownership Shape architecture, modular services, and engineering culture from day one.
Scale + Complexity You'll design systems that operate on thousands of records, across multi-client, multi-agent environments-with LLMs at the core.
Early Team, High Growth Be part of a tight-knit, mission-oriented team, and grow into our
Backend Lead Engineer
as we scale.
What We Offer
Compensation : Competitive salary + equity package Health & wellness support
- Stipend + medical (vision, dental, health) insurance coverage Unlimited PTO
- Recharge when you need to High learning velocity
- Get exposed to AI, infra, GTM, and real customers daily
We often celebrate the final moment: a patient receiving a life-saving therapy or a groundbreaking treatment becoming standard of care. But behind that moment is a complex, coordinated effort that begins years earlier.
Pharmaceutical and med device companies shoulder this responsibility every day:
Advancing science from lab to clinic Navigating regulatory and access barriers Ensuring safe, evidence-based adoption in the real world They're not just bringing products to market; they're shaping the future of care.
Yet these organizations are often held back by outdated workflows and siloed data, unable to fully harness the knowledge that already exists across their teams.
Atrix was built to change that.
We exist to support the mission of those who dedicate their lives to creating and delivering innovations that impact global health.
The Role Description
You'll be a
core builder of Atrix's backend infrastructure , powering AI-native workflows that ingest unstructured data, structure it with AI, and deliver insights that matter-instantly and reliably.
You'll work on
scalable data pipelines, robust APIs, and real-time inference systems , supporting everything from complex agent workflows to customer-facing dashboards. Whether it's building retrieval pipelines, optimizing async background workers, or designing clean, secure APIs, your work will be foundational to how our platform works and scales.
We're building a
modular, agentic platform
that connects to customer-approved data sources, transforms unstructured data using LLM-based agents, and delivers decision-ready intelligence to regulated teams.
You'll tackle rich backend engineering challenges like:
System Design & Reliability
- Scale to handle massive amounts of records with fast response times LLM Ops
- Make AI outputs explainable, auditable, and efficient Multi-Tenant Infra
- Isolate customer data across parallelized pipelines AI Performance Tuning
- Optimize inference cost, caching, and latency RAG Pipelines & Contextual Workflows
- Connect structured + unstructured data for real-world usage You'll work closely with the
Engineering Lead and CEO , and collaborate across product, AI, and GTM. As one of our
earliest backend engineers , you'll influence everything from our architecture to hiring bar.
This is an
in-person role based in NYC , with flexibility for remote work on some days as needed.
Responsibilities
This role is perfect for someone who thrives on solving deep technical problems, loves optimizing systems for speed and scale, and gets energized by seeing their work used in real-world, high-stakes environments. If you're excited about powering AI workflows behind the scenes-and building infrastructure that's as elegant as it is reliable-we'd love to talk.
In this role, you will:
Design and own major modules of our backend architecture (APIs, workers, orchestration) Optimize performance and reliability of data processing and AI inference systems Build and maintain LLM-powered backend features and multi-step workflows Collaborate with product and AI teams to launch performant, production-grade AI features Improve observability, traceability, and modularity of backend systems Lead customer-focused feature delivery with high attention to security and compliance Must haves
5+ years backend engineering experience in fast-paced product teams 2+ years of Python experience, including async programming Expertise with one or more frameworks: FastAPI, Flask, Django Strong experience with SQL (PostgreSQL) and ORMs (SQLAlchemy or equivalent) Experience building APIs, background workers, and distributed systems Understanding of how LLMs, embeddings, or RAG workflows function Startup experience or demonstrated ownership in complex backend projects Nice to haves
Familiarity with Celery, LangChain, LlamaIndex, or other LLM orchestration tools Exposure to RAG or context injection workflows Experience with AWS, Terraform, Kafka, or PyTorch Background in healthcare, data security, or regulated environments Why Join Atrix as a Backend Engineer?
Mission-Driven Impact Your code will help life sciences teams deliver better treatments-faster. Every system you build supports real-world clinical outcomes.
Real AI, Real Stakes This isn't research tooling. You'll make AI work for real customers-ensuring reliability, explainability, and speed in high-stakes environments.
Deep Backend Ownership Shape architecture, modular services, and engineering culture from day one.
Scale + Complexity You'll design systems that operate on thousands of records, across multi-client, multi-agent environments-with LLMs at the core.
Early Team, High Growth Be part of a tight-knit, mission-oriented team, and grow into our
Backend Lead Engineer
as we scale.
What We Offer
Compensation : Competitive salary + equity package Health & wellness support
- Stipend + medical (vision, dental, health) insurance coverage Unlimited PTO
- Recharge when you need to High learning velocity
- Get exposed to AI, infra, GTM, and real customers daily